Media and data, wedded together for better or for worse
Media organisations have always had a passionate relationship with data, in every sense of the word. While passion originally referred to a kind of suffering to be endured, in modern language it has come to mean an all-consuming love. Digital media endures and suffers in this new attention economy founded on data, under the crushing weight of the Facebook/Google duopoly. More than ever, digital media groups need to understand and draw value from their own audiences. The challenge is therefore twofold: how to draw value from audience data, all while avoiding head-on combat with platforms on their territories — privacy minefields lacking in journalistic ethics.
For media groups, digital data is essential to creating value for three reasons: it guarantees/ensures the power of your reach, it makes it possible to qualify your audience (and to target your ads), and finally, it provides a greater understanding of your audience and how to better serve them.
If data is to serve these three purposes, it requires one often problematic element: trust.
- First of all, to use data, you must earn the trust of Internet users. Data must be collected for transparent and proportional purposes. It’s fundamental to not share this precious data with shady players (even if that means passing up short-term profits), and even more so if they are competitors. In this regard, even if Facebook, Google and company are technically unavoidable as audience sources, they’re far from being highly recommendable, because of their nearly unlimited capacity to combine data, and because of their business model. The GDPR has now set a framework (even if that framework still must be clarified). Media groups must be wary of surveillance capitalism which would relegate them to a position of servitude and break the trusting relationship they have built with their audiences.
- You must also ensure that you can trust the data itself, if you wish to extract solid and lasting value. Digital device analytics and measurement are far from having a binary reliability. Today’s complex and ever-evolving environment, along with the multiplication of devices, requires thoroughness and rigour that are often neglected. It’s therefore crucial to have strict quality processes to ensure uniform measurement of audiences and accurate visibility into ad space. It’s a complex, dull and thankless task at times — it’s not very exciting to verify the reliability of tagging plans or to scrub bot traffic, but this meticulousness is non-negotiable if you want the credible measurements that the market expects. While independent reference organisations are sometimes criticised, their position as trusted third-parties is as complex as it is essential to prevent the dominant players from imposing groundless, unverifiable measurements which lead to repeated scandals (the most recent examples being video measurement on YouTube and Facebook).
- Finally, you must ensure internal trust in the data, amongst your teams. You must educate people and democratise access to data in order to establish robust and impartial data governance. Your analytics tools will only truly be accepted and used to inform strategic choices if the data offers a level of reliability and consistency that’s accepted by everyone, from top management to operations teams to journalists and other content creators.
Data is a precious and sensitive raw material, essential to creating value for media groups, but also a Faustian temptation. In a ferociously competitive environment where two dominant players absorb nearly 70% of revenues and 95% of growth, it could be tempting to copy their business model via hyper-personalisation of content, by selling personal data and highly intimate information to the highest bidder. But it’s also possible to choose a bolder route by using data in an ethical way, by favouring transparency, by improving the user experience, and by not biasing the (necessary) information hierarchy.
It’s important to re-establish the logical (and democratic) relationship of power between media groups and ad platforms. Before they produce data, media groups first and foremost produce and publish content. Data must serve content — and not the other way around.
